The research laboratory often serves as a window to the future of medicine. Despite the cutting-edge capabilities of the modern laboratory, engineers who design these facilities sometimes use methodologies that are scientifically unsound. While most engineering design methodologies are founded on scientific methods, there are at least two that are not: piped utilities and HVAC systems.

Laboratory piped-utility systems encompass the central equipment and distribution systems needed to deliver such services as compressed air, natural gas, vacuum, pure water, and process cooling to each laboratory work area. HVAC systems include the central equipment and distribution systems needed to provide comfort, ventilation, and the required offset pressurization conditions for each laboratory relative to their adjacent work areas.

Together, these systems are responsible for approximately 25% of initial construction costs and 50% of annual energy costs for all laboratory facilities. With such a staggering amount of money at stake, the design of these systems should be subjected to a high degree of scientific analysis to ensure that their sizing is as precise as possible, and the load forecasts are accurate. Unfortunately, this could not be further from reality.

For the past 20 years, the methods associated with sizing these systems were handled using unverified benchmarking tables to estimate internal heat gains, as well as simultaneous-use-factor tables to size piped utilities-methods founded largely on speculation and conjecture. While virtually every aspect of engineering is supported by solid scientific principle, unverified benchmarking takes a mere 30 seconds to achieve and has no scientific underpinning. Rather than determining the specific design needs for a certain facility, this type of benchmarking draws from a database of previous jobs, assuming that if something was applied previously without mishap, it must be suitable for the next project.

What unfortunately follows is a building infrastructure that is grossly oversized from approximately 40% to as much as 300%. The end result is a staggering increase in construction costs, averaging $30 per square foot. This is calculated as a result in a few different factors: inconsistency from benchmarking table to table and inherent problems in the way the tables themselves were put together, among others. Oversizing also leads to excessive long-term energy costs from operating inefficient building systems-costs that are, at a minimum, equal to the unnecessary construction costs expended in the first place. This is money that could be better spent on the procurement of cutting-edge scientific equipment or additional research personnel.

While many in the design community are aware of this dilemma, the ability to accurately estimate loads to appropriately size systems has eluded engineers for decades. Our firm employs a unique solution using probability theory, a scientifically proven method that uses a methodology dating back to the 17th century. The probability theory has already been successfully implemented in an array of scientific and engineering applications, ranging from projecting traffic flows to manufacturing controls, to the Hunter’s curve (figure) used in plumbing system design.

We have successfully applied this method in laboratory design and named it Outcome PBA™. Outcome PBA can be applied effectively to the design of both new laboratory facilities or during the renovation of existing laboratories. In our experience, it has led to an average savings of $30 per square foot and has reduced operational costs.

Outcome PBA has been applied to a variety of projects, including the University of California, Riverside Geology and Physics Building renovation and UCLA’s Life Sciences Research Building. The cost associated with it is approximately $0.50 per square foot.

Probability theory is used on every project by every mechanical engineer in, for example, the sizing of plumbing water supply and drainage systems and determining peak water-flow demands. For example, the Hunter’s curve is employed to determine peak water demand flow under the principle that the size of plumbing systems should not depend on the premise that all toilets will flush simultaneously, and that simultaneous flushing of the correct number of toilets can be calculated. By using probability theory in lab design, which is based on the same principles as the Hunter’s curve, we have been able to predict the simultaneous use of piped utilities and the simultaneous internal heat gains from laboratory equipment.

This prediction is accomplished by applying a mathematical equation that takes into account the total number of fixtures that are installed in a laboratory space. Then the total number of fixtures that are likely to be used simultaneously is calculated based on usage factors that are quantitatively established during lab programming. The calculation is performed for each service, the type of lab, lab function, operating hours, and several other variables, to ascertain the factor to be applied for the particular lab.

The result is a properly sized system that saves construction, operating, and maintenance costs and better meets the lab’s energy demands in an affordable and efficient manner. As healthcare systems continue to endeavor to improve the operations of their laboratories, probability-based analysis represents the most efficient and cost-effective way to ensure that the least amount of money necessary is expended on building and maintaining medical labs, and that funds overall are used appropriately to finance research and advancement. HD